Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications covers timely topics, including the neural network (NN), particle swarm optimization (PSO), evolutionary algorithm (GA), fuzzy sets (FS) and rough sets (RS), etc. Furthermore, the book highlights recent research on representative techniques to elaborate how a data-centric system formed a powerful platform for the processing of cloud hosted multimedia big data and how it could be analyzed, processed and characterized by CI. The book also provides a view on how techniques in CI can offer solutions in modeling, relationship pattern recognition, clustering and other problems in bioengineering.
It is written for domain experts and developers who want to understand and explore the application of computational intelligence aspects (opportunities and challenges) for design and development of a data-centric system in the context of multimedia cloud, big data era and its related applications, such as smarter healthcare, homeland security, traffic control trading analysis and telecom, etc. Researchers and PhD students exploring the significance of data centric systems in the next paradigm of computing will find this book extremely useful.
1. Cover image - p. iv 2. Title page - p. iv 3. Table of Contents - p. iv 4. Copyright - p. iv 5. Contributors - p. xiii 6. Foreword - p. xvii 7. Preface - p. xix 8. Chapter 1: A Cloud-Based Big Data System To Support Visually Impaired People - p. xxii 9. Chapter 2: Computational Intelligence in Smart Grid Environment - p. 22 10. Chapter 3: Patient Facial Emotion Recognition and Sentiment Analysis Using Secure Cloud With Hardware Acceleration - p. 59 11. Chapter 4: Novel Computational Intelligence Techniques for Automatic Pain Detection and Pain Intensity Level Estimation From Facial Expressions Using Distributed Computing for Big Data - p. 89 12. Chapter 5: Computational Intelligence Enabling the Development of Efficient Clinical Decision Support Systems: Case Study of Heart Failure - p. 121 13. Chapter 6: Aspect Oriented Modeling of Missing Data Imputation for Internet of Things (IoT) Based Healthcare Infrastructure - p. 133 14. Chapter 7: A Hybrid Computational Intelligence Decision Making Model for Multimedia Cloud Based Applications - p. 145 15. Chapter 8: Energy-Constrained Workflow Scheduling in Cloud Using E-DSOS Algorithm - p. 157 16. Chapter 9: Producing Better Disaster Management Plan in Post-Disaster Situation Using Social Media Mining - p. 169 17. Chapter 10: Metaheuristic Algorithms: A Comprehensive Review - p. 183 18. Chapter 11: Unsupervised Anomaly Detection for High Dimensional Data—an Exploratory Analysis - p. 231 19. Chapter 12: Fog – Driven Healthcare Framework for Security Analysis - p. 251 20. Chapter 13: Medical Quality of Service Optimization Over Internet of Multimedia Things - p. 270 21. Chapter 14: Energy-Efficiency of Tools and Applications on Internet - p. 295 22. Chapter 15: Transforming Healthcare Via Big Data Analytics - p. 318 23. Index - p. 335
Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications covers timely topics, including the neural network (NN), particle swarm optimization (PSO), evolutionary algorithm (GA), fuzzy sets (FS) and rough sets (RS), etc. Furthermore, the book highlights recent research on representative techniques to elaborate how a data-centric system formed a powerful platform for the processing of cloud hosted multimedia big data and how it could be analyzed, processed and characterized by CI. The book also provides a view on how techniques in CI can offer solutions in modeling, relationship pattern recognition, clustering and other problems in bioengineering.
It is written for domain experts and developers who want to understand and explore the application of computational intelligence aspects (opportunities and challenges) for design and development of a data-centric system in the context of multimedia cloud, big data era and its related applications, such as smarter healthcare, homeland security, traffic control trading analysis and telecom, etc. Researchers and PhD students exploring the significance of data centric systems in the next paradigm of computing will find this book extremely useful.
1. Cover image - p. iv 2. Title page - p. iv 3. Table of Contents - p. iv 4. Copyright - p. iv 5. Contributors - p. xiii 6. Foreword - p. xvii 7. Preface - p. xix 8. Chapter 1: A Cloud-Based Big Data System To Support Visually Impaired People - p. xxii 9. Chapter 2: Computational Intelligence in Smart Grid Environment - p. 22 10. Chapter 3: Patient Facial Emotion Recognition and Sentiment Analysis Using Secure Cloud With Hardware Acceleration - p. 59 11. Chapter 4: Novel Computational Intelligence Techniques for Automatic Pain Detection and Pain Intensity Level Estimation From Facial Expressions Using Distributed Computing for Big Data - p. 89 12. Chapter 5: Computational Intelligence Enabling the Development of Efficient Clinical Decision Support Systems: Case Study of Heart Failure - p. 121 13. Chapter 6: Aspect Oriented Modeling of Missing Data Imputation for Internet of Things (IoT) Based Healthcare Infrastructure - p. 133 14. Chapter 7: A Hybrid Computational Intelligence Decision Making Model for Multimedia Cloud Based Applications - p. 145 15. Chapter 8: Energy-Constrained Workflow Scheduling in Cloud Using E-DSOS Algorithm - p. 157 16. Chapter 9: Producing Better Disaster Management Plan in Post-Disaster Situation Using Social Media Mining - p. 169 17. Chapter 10: Metaheuristic Algorithms: A Comprehensive Review - p. 183 18. Chapter 11: Unsupervised Anomaly Detection for High Dimensional Data—an Exploratory Analysis - p. 231 19. Chapter 12: Fog – Driven Healthcare Framework for Security Analysis - p. 251 20. Chapter 13: Medical Quality of Service Optimization Over Internet of Multimedia Things - p. 270 21. Chapter 14: Energy-Efficiency of Tools and Applications on Internet - p. 295 22. Chapter 15: Transforming Healthcare Via Big Data Analytics - p. 318 23. Index - p. 335
